Installation

ZhuSuan is still under development. Before the first stable release (1.0), please clone the repository and run

pip install .

in the main directory. This will install ZhuSuan and its dependencies automatically. ZhuSuan also requires TensorFlow 1.13.0 or later. Because users should choose whether to install the cpu or gpu version of TensorFlow, we do not include it in the dependencies. SeeInstalling TensorFlow.

If you are developing ZhuSuan, you may want to install in an "editable" or "develop" mode. Please refer to the Contributing section below.

Documentation

• Tutorials and API docs

• ZhuSuan's white paper

Examples

We provide examples on traditional hierarchical Bayesian models and recent deep generative models.

To run the provided examples, you may need extra dependencies to be installed. This can be done by

pip install ".[examples]"

• Gaussian:HMC

• Toy 2D Intractable Posterior:SGVB

• Bayesian Neural Networks:SGVB,SGMCMC

• Variational Autoencoder (VAE):SGVB,IWAE

• Convolutional VAE:SGVB

• Semi-supervised VAE (Kingma, 2014):SGVB,Adaptive IS

• Deep Sigmoid Belief NetworksAdaptive IS,VIMCO

• Logistic Normal Topic Model:HMC

• Probabilistic Matrix Factorization:HMC

• Sparse Variational Gaussian Process:SGVB

Citing ZhuSuan

If you find ZhuSuan useful, please cite it in your publications. We provide a BibTeX entry of the ZhuSuan white paper below.

@ARTICLE{zhusuan2017,
    title={Zhu{S}uan: A Library for {B}ayesian Deep Learning},
    author={Shi, Jiaxin and Chen, Jianfei. and Zhu, Jun and Sun, Shengyang
    and Luo, Yucen and Gu, Yihong and Zhou, Yuhao},
    journal={arXiv preprint arXiv:1709.05870},
    year=2017,
}

Contributing

We always welcome contributions to help make ZhuSuan better. If you would like to contribute, please check out the guidelines here.